System and method for non-invasive real time assessment of cardiovascular blood pressure

ABSTRACT

A system and method for non-invasive medical imaging based measurement and calculation of the cardiovascular pressure is presented, wherein the pressure measurements are performed by means of the image stream processing estimating the volumes of the oscillating traceable regions within the body. The invention is applicable to any part of the body transparent for imaging device capable to produce real-time image series. The image series is then processed to obtain the pressure values within the cardiovascular system. The invention permits to assess non-invasively and in real time the pressure in any part of the heart and large blood vessels, and calculate the major markers of heart failure, cardiomyopathy, ventricular ischemia, infarction and other heart related diseases.

PRESENT FIELD

The present invention belongs to the field of medical imaging for the non-invasive real time determination of a cardiovascular blood pressure.

BACKGROUND

Diseases including congestive heart failure (CHF), abdominal aortic aneurysm (AAA), pulmonary artery hypertension (PAH), are a major cause of premature death. There is a desire to be able to provide an advantageous monitoring of intravascular and/or intracardial blood pressure, including continuous monitoring. Based on such blood pressure measurements, diagnosis and treatment of patients can be based on a unique level, preventing substantial populations of patients from premature death.

In general, implantable sensors used for such monitoring are introduced via endovascular techniques. Such invasive measurement of intra-cardiac pressure is desired to be minimized due to complexity of the procedure and related patient risk.

There are two types of implantable sensors. Active implantable sensors that need a rechargeable energy source, which is undesired and related to a number of apparent disadvantages. Passive implantable sensors which are typically electromagnetic, providing an electromagnetic signal when irradiated from the external to the human body source of electromagnetic energy mainly in radio frequencies (RF). These sensors have a considerable drawback due to the locality of their position and ability to measure the pressure only in their circumference, also these sensors have electronics incorporated and have thus related disadvantages, such as questions of biocompatibility, size or reliability of the implanted sensor over time. Moreover, while a part of the RF energy is absorbed by the implanted RF sensor, parts of the RF energy are absorbed by the body which may cause potential problems in living organisms. Energy transmitted from outside the body may be converted in these implants to power the electronics, make measurements and transmit measurement results back to the outer detecting system. Such detecting system, positioned external to the human body registers the electromagnetic field irradiated in its turn by the circuit of the implanted sensor.

An example of electromagnetic sensors is described in the U.S. Pat. No. 7,245,117 B1 with the title “Communicating with implanted wireless sensor”, the resonant frequency of a sensor is determined for energizing the system to burst the RF energy at predetermined frequencies and amplitudes. A similar technology is described in the U.S. Pat. No. 8,894,582 B2.

Cardiovascular ultrasound measurements are known, but restricted to either catheter based ultrasound transceivers introduced into the body, or imaging and Doppler ultrasound measurements. Blood pressure in peripheral vessels may be measured non-invasively from the outside of the body using ultrasound. However, calibration to actual pressure values of such ultrasound-based methods is complex and not always reliable. Moreover, such methods cannot selectively measure pressure at specific depths and places in the body, e.g. in the aorta or the heart. Other, non-invasive techniques include methods to examine dimensions of blood vessels, or methods based on examining blood flow and are based on Doppler ultrasound or other ultrasound imaging methods, as disclosed, for instance, in U.S. Pat. Nos. 5,411,028, 5,477,858 A, 5,544,656, 6,814,702 B2, 5,724,973 A, US 20140081144 A1, EP 1421905 A1, U.S. Pat. No. 7,128,713 B2, WO 2007087522 A2, US 20080119741 A1, U.S. Pat. No. 7,736,314 B2, US 20130197367 A1, or US 20130006112.

For example in U.S. Pat. No. 5,520,185 A with the title “Method for recognition and reduction of blood speckle in blood vessel imaging system”, a method for enhancing an intravascular ultrasound blood vessel image system is disclosed. It is explained how ultrasound echoes representing vessel walls are distinguished from ultrasound echoes from blood flow by using a classifier which employs the mean and variance of the raw data of greyscale intensities as acquired directly from an ultrasound scanner-detector.

In U.S. Pat. No. 5,800,356 with the title “Ultrasonic diagnostic imaging system with Doppler assisted tracking of tissue motion”, a method for tracing the border of tissue through temporarily acquired scan lines using velocity information corresponding to the tissue edges to trace the denoted border is disclosed.

In U.S. Pat. No. 6,258,031 B1 with the title “Ultrasound diagnostic apparatus”, the velocity of a blood flow and velocity of a blood walls at the same time are measured by an ultrasound with phase detecting.

In US 20090171205 A1 with the title “Method and system for locating blood vessels”, a method utilizing the direct ultrasound sounding for detecting the blood vessels and precisely determining of their depth and diameter is disclosed.

In U.S. Pat. No. 8,469,887 B2 with the title “Method and apparatus for flow parameter imaging”, a method using pulse-wave spectral Doppler imaging allowed to obtain an ultrasound image as a sectional image of the blood vessel, including the inner and outer walls.

Other methods and systems for blood pressure measurements in the blood vessels using Doppler ultrasound imaging are disclosed in: U.S. Pat. No. 5,749,364 A1, WO 20010000 A9, US 20070016037 A1, US 20050015009 A1, US 20140180114 A1, US 20140148702, U.S. Pat. No. 8,968,203 B2, US 20150289836.

In US 20150230774 A1 with the title “Blood pressure monitor and method”, non-invasive continuous real-time monitoring of an arterial blood pressure is disclosed using Doppler probes for systolic and diastolic blood pressure.

In the patent U.S. Pat. No. 7,404,800B2 a hybrid LVEDP monitor is disclosed. The patent refers to unspecified non-invasive pressure measurement devices (“barographs”), yet does not disclose how they produce the “pressure waveform” that is therein used for subsequent analysis and unlike current disclosure does not rely on multi-dimensional image processing.

The above discussed non-invasive ultrasound or Doppler ultrasound methods for the examination of the blood vessels have a number of explicit deficiencies and it is desirous to overcome each of these deficiencies, alone or in combination. Deficiencies include but are not limited to the below:

1. Reproducibility and accuracy of the examination of the blood vessel is highly dependent on the correct orientation of the ultrasound beam's propagation direction (the axis of the ultrasound transducer) relatively to the vessel's longitudinal axis being interrogated. The speed of blood flow is measured by converting of the value of the shift of the Doppler frequency if using the Doppler equation:

V=(c×Δf)/(2f ₀×cos α),

where V is the velocity of the blood flow, c is the speed of sound in the tissue, f ₀ is the initial frequency of the signal, and α is the angle between the direction of the blood flow and the axis of the ultrasound beam. The angle α strongly affects the value of the measured Doppler frequency Δf which in turn is used to calculate of the speed of the organic reflectors in the blood flow.

2. Reliability and precision of blood vessel examination including blood pressure measurement based on ultrasound can be improved. For instance, the Doppler frequency spectra display the blood flow information from a certain area at a given depth, (control volume), and do not provide information about blood flow in other parts of the vessel which are visible on the ultrasound image. Therefore, in case choosing an inadequate control volume (ex., when cos α˜0) all diagnostic information will be incorrect.

3. References to non-specified devices and amplitude sensors (such as in U.S. Pat. No. 7,404,800B2) that produce the intracardiac pressure without further explanations.

Insufficient accuracy of results from hemodynamic measurements in blood vessels using certain Doppler methods are well documented. For example, in: S. B. Coffi, D. Th. Ubbink and D. A. Legemate. Non-invasive Techniques to Detect Subcritical Iliac Artery Stenosis. Eur. J. Vascular and Endovascular Surgery, 29, 2005; Ricardo Cesar, Rocha Moreira. Comparative study of Doppler ultrasonography with arteriography in the evaluation of aortic occlusive disease. Journal Vascular Brasileiro, 8, January/March 2009; or Vilhelm Schaberle. Ultrasonography in Vascular Diagnosis. A Therapy-Oriented Textbook and Atlas. Second Edition. Springer Heidelberg-Dordrecht-London-New-York, 2011.

The article Gernot Schulte-Altedorneburg, Dirk W. Droste, Szabolcs Felszegny, Monica Kellerman et al., Accuracy in vivo Carotid B-mode Ultrasound Compared with Pathological Analysis: Intima-Media Thickening, Lumen Diameter and Cross-Sectional Area. Stroke: Journal of the American Heart Association, 2001 demonstrates an insufficient accuracy of the results obtained for the examination of blood vessels using of the ultrasound B-mode imaging only.

Several patents are dedicated to using passive sensors placed in the human body and interacting with an external ultrasound source for analysis of physiological parameters of the human organism, as for instance U.S. Pat. Nos. 5,619,997 A, 5,989,190 A, 6,083,165 A, or US 20030176789 A1. However, these devices and methods have a number of drawbacks, namely the following:

1. The disclosures in patents U.S. Pat. Nos. 5,619,997 A, 5,989,190 A, 6,083,165 A consist in the suggestion that the physical parameters (pressure, temperature, viscosity) defining the state of the medium (including the human body) are determined as a functional relationship P=f(v), where P is the physical parameter and v is the frequency of the ultrasound wave reflected by a passive sensor placed in the medium which is different from the frequency of the primary ultrasound beam due the energy absorption by the sensor.

2. The disclosure in patent application US 20030176789 A1 suggests that the value of a specific physical parameter, such as the pressure, associated with the specific state of any medium (including the human body) is determined as the result of the frequency analysis of the acoustic signal reflected by the passive sensor implanted into the medium. The passive sensor has to be equipped with two parallel to each other reflective surfaces and the reflected signal is the result of the interference of the two acoustic signals: the first signal is reflected by the first reflective surface and second signal reflected by the second reflective surface.

The frequency analysis of the resultant signal permits allocate the frequencies of the maximal attenuation of the intensity and the value of the specific physical parameter is determined on the basis of the correlation relationships between the values of the parameters and the frequencies of the maximum attenuation of the resultant signal. The knowledge of the correlation between the values of the parameters and the frequencies is not sufficient to determine the functional relationship P=F(v). The method is dependent of the frequencies of both the direct and reflected signals, It is desired to provide a more simple method and system that is independent of the frequencies of both the direct and reflected signals which are also present in the following patent: US 20070208293 A1 “Methods and devices for non-invasive pressure measurement in ventricular shunts”. This disclosure relates to a ventricular shunt including a pressure-sensitive body that changes its dimensions in response to the pressure of the cerebrospinal fluid within the shunt.

The difference of US 20070208293 A1 from current document lies in several aspects. First, the flow of cerebrospinal fluid is quasi-stationary unlike the turbulent blood flow such as inside the heart chambers which are dealt with in the current disclosure. Second, the system from US 20070208293 A1 is tracking the distance changes between the transducer and ultrasonic beam reflecting gas-filled capsule, while in the current description the pressure is determined/estimated as the function of volumes of oscillating traceable regions in a series of images produced by medical imaging device placed fully outside of the body, regardless of presence or absence of any implanted devices. By an oscillating traceable region we mean a region appearing on most images of the series corresponding to the physiological domain where the pressure is measured or calculated, typically one or more of heart chambers, pulmonary artery and/or aorta.

On the other hand, we note the successful approach of the linear regression modeling of the maximal value of the Left Atrium pressure changes through the simultaneous measurements of the Left Atrium pressure with a catheter and trans-esophageal Doppler echocardiography published in the article “Noninvasive assessment of left atrial maximum dP/dt by a combination of transmitral and pulmonary venous flow”, see the Journal of the American College of Cardiology, V. 34, Issue 3, September 1999, P. 795-801, by Satoshi Nakatani, Mario J Garcia, Michael S Firstenberg, Leonardo Rodriguez, Richard A Grimm, Neil L Greenberg, Patrick M McCarthy. However, in this article it had not been reflected that not only Doppler echocardiography but a regular ultrasound or other imaging methods can be used to assess the atrial and more important ventricular (both left and right maximal dP/dt values called Left/Right Ventricular Pressure Rise) blood pressure and not only pressure changes, but absolute pressure values as well. This principle is realized in the present invention.

This present disclosure contains amongst others a novel method to calculate and determine said pressure and said method is independent of the frequencies of both the direct and reflected signals. Thus, prior technical solutions, such as disclosed in U.S. Pat. Nos. 5,619,997 A, 5,989,190 A, 6,083,165 A, or US 20030176789 are not analogues both in the methods of data collection and the methods of data processing of the current disclosure.

The approach in the present disclosure is based on the estimation of the pressure as a function of volumes of oscillating traceable regions (e.g. heart chambers) conducted via image processing of ultrasound (or other imaging device with similar functionality) recording.

Additionally, the present disclosure contains a provision for utilizing real-world data for increasing performance and accuracy obtained by calibration process, which contains initial synchronized simultaneous measurement recordings of the intra-cardiac blood pressure, such as with a micro-manometer catheter, and imaging device recordings, performed in case a patient undergoes a cardiac catheterization for any medical reason.

SUMMARY OF THE INVENTION

The essence of the current disclosure lies in the development of a direct non-invasive method of measurement of the blood pressure in the heart or a blood vessel and an apparatus for its practical implementation.

The present invention relies on the a usage of medical imaging devices capable to produce a time series of images displaying the boundaries, shape, size and position of inner physiological features such as heart chambers while being positioned fully outside of the body and communicating the said series of images in real time to a controlling device for subsequent processing.

The present invention is defined by the enclosed patent claims. The advantages of the disclosed method over the prior art presented by this disclosure include:

-   -   Process for the analysis of a series of images using the new         notions of:         -   T-image defined as a chronological union of said initial             image stream. In the case of ultrasound imaging T-image             corresponds the unification of all M-modes in image stream             over the time,         -   Characteristic (or Eigen-) image as an invariant of the             T-image which is used to identify the pressure curve inside             said T-image and speed up calculation processing.     -   Prediction of pressure data changes as function of the estimated         volume changes during non-invasive measurements;     -   Calibration procedure, performed as synchronized, simultaneous         measurements of intra-cardiac blood pressure with a         micro-manometer catheter and a medical imaging device with         subsequent image processing analysis and model fit;     -   Usage of fitted parameters from the above calibration procedure         to evaluate the imaging data anytime, anywhere not only for an         individual patient, but for a class of patients with similar         physiological profile.

The method of the disclosure comprises a set of processes for pressure measurement based on the stream of images obtained in a non-invasive manner by an imaging device to estimate volumes of oscillating traceable regions in the stream of images.

A software comprising an algorithm for performing such pressure determination method is provided. Said software is preferably stored on a computer readable medium.

The present disclosure provides systems, methods, devices and software that permit to directly measure pressure and its dynamic changes inside a body from the outside of the body without the need of any implanted device.

The key novelties of the current disclosure are contained in the notions of the

-   -   T-image {T_(i)}_(i=1, . . . N) defined as a chronological union         of said initial image stream {J_(i)}_(i=1, . . . N) with         corresponding time stamps. In case of Ultrasound Imaging it can         be represented directly in cylindrical coordinates as one object         (called manifold in Differential Geometry).     -   Characteristic (or Eigen-) Image {I_(i)}_(i=1, . . . N) of the         said T-image {T_(i)}_(i=1, . . . N) which is defined as a         chronological union of the averages of the rows or other         invariants of the initial image series {T_(i)}_(i=1, . . . N)         across each given depth, in the way that the first pixel-column         I₁ (i=1) of the Characteristic image contains the averages over         the rows or other invariants of the first image in time, the         second pixel-column I₂ (i=2) of the Characteristic image         contains the averages over the rows or other invariants of the         second image in time, and finally the last pixel-column I_(N)         (i=N) of the Characteristic image contains the averages over the         rows or other invariants of the last image in time in the         series. Characteristic image method reduces the problem         dimensionality while still permits to identify the pressure         curve, provides a considerable boost in performance and lowers         calculation power requirements which is useful for small or         embedded devices.     -   The invariants in the Characteristic images can be         -   averages of the columns         -   vertical or horizontal average gradients         -   singular values or eigenvalues of each image packed into the             Characteristic image as one matrix         -   Fourier, Wavelet or other generalized decomposition images             of the Characteristic images defined above.

For said Calculation or determination, the pressure P inside an oscillating traceable region in the body will be defined as the best fit function to the measured or estimated pressure values P_(i)≈P(t_(i), {T_(i)}_(i=1, . . . N)) of a shape and position of the said oscillating traceable region.

In case of using T-Image {T_(i)}_(i=1, . . . N), the function is P(t_(i))=P(t_(i), {x_(j)}_(j=1, . . . M) ^(i)⊂T_(i)), where x_(j) are a set of coordinate parameters representing the said oscillating traceable region boundaries and position at each time corresponding to each frame T_(i) of the said T-image {T_(i)}_(i=1, . . . N).

In case of using Characteristic image {I_(i)}_(i=1, . . . N) of the said T-image {T_(i)}_(i=1, . . N), a process which simplifies the model reducing its dimension and significantly improves calculation times without significant precision loss, P_(i)=P(t_(i), {x_(j)}_(j=1, . . . K) ^(i)⊂I_(i)), where {x_(j)}_(j=1, . . . K) are a set of coordinate parameters representing the said oscillating traceable region size and position at each time corresponding to each column I_(i) of the said Characteristic Image {I_(i)}_(i=1, . . . N) representing the said oscillating traceable region size and position at each time corresponding to each column I_(i) of the said Characteristic Image {I_(i)}_(i=1, . . . N).

The present disclosure contains a provision for utilizing real-world data for increasing performance and accuracy.

The real-world data is obtained by calibration process, which contains initial synchronized simultaneous measurement recordings of the intra-cardiac blood pressure with penetrating sensor, such as with a micro-manometer catheter, and imaging device recordings, performed in case a patient undergoes a cardiac catheterization for any medical reason independent of the usage of the present system and subsequent fitting of the parameters of the mathematical model to calculate the pressure function according to the measured, real-time absolute pressure values.

Through Calibration process, the directly measured intra-cardiac chamber pressures during catheterisation are aligned with synchronised imaging data.

Thus, when the system is calibrated, the (blood) pressure and its dynamic changes within the body, such as in a blood vessel can be calculated with high accuracy and stability anytime when a recording of the calibrated region is provided with the medical imaging device connected to the current system. The fitted mathematical models produced by the calibration process on various patients enables to produce generalized mathematical models to be applied to patients that have not undergone the calibration process but have similar physiological characteristics to those that were calibrated.

The present disclosure further provides an example of a system for subsequent calibration, measurements and calculations of the blood pressure based on the volume of cardiovascular structures including but not limited to the left atrium (LA), right atrium (RA), left ventricle (LV), right ventricle (RV), the pulmonary artery (PA) or the pulmonary artery wedge (PAW). During the calibration the pressure values P_(i) of the oscillating traceable regions at time moments t_(i) are measures by direct pressure meters, such as catheter based blood pressure sensors connected to a pressure monitor unit. The imaging is provided simultaneously by a medical imaging device. Both intra body pressure meter measurement data and image stream {J_(i)}_(i=1, . . . N) over time are synchronously recorded into the system and optimally regressed to a function P of a given shape in the way that P_(i)≈P(t_(i), {T_(i)}_(i=1, . . . N)), where T-image {T_(i)}_(i=1, . . . N) is defined as a chronological union of said initial image stream {J_(i)}_(i=1, . . . N) with corresponding time stamps t_(i).

When the system is calibrated, the calculation is based on the utilization of the function P=P(t_(i), {T_(i)}_(i=1, . . . N)) from previous calibration process: the non-invasive ultrasound measurement with an ultrasound apparatus is provided with further image processing derivation of the set of coordinate parameters {x_(j)}_(j=1, . . . M) representing the said oscillating traceable region size and position. The further substitution into the formula P(t_(i))=P(t_(i), {x_(j)}_(j=1, . . . M) ^(i)⊂T_(i)) gives the real time pressure and pressure changes while the series of ultrasound images is recorded. In the absence of calibration for a particular patient machine-learning tools permit to estimate the pressure basing on calibration data from other patients with similar physiological parameters.

The above determined pressure values may provide valuable diagnostic information for potential therapeutical treatment of a patient, for example, based on RV (Right Ventricle) direct pressure measurement during calibration process, the method permits to assess non-invasively during the subsequent Ultrasound recordings the RVEDP—right ventricular end-diastolic pressure being the major marker of the right heart failure, cardiomyopathy, RV ischemia and infarction.

In the same way based on LV (Right Ventricle) or PAW (Pulmonary Artery Wedge) direct pressure measurement during calibration process, the method permits to assess non-invasively during the subsequent Ultrasound recordings the LVEDP—left ventricular end-diastolic pressure being the major marker of the left heart failure (CHF), myocardial infarction, tamponade, aortic regurgitation and others.

The achieved in this way real-time LVEDP/RVEDP ratio can be an independent marker for cardiac output response during Adaptive Servo-Ventilation therapy in Patients with heart failure.

The other real time characteristics which can be measured or estimated using the above method include but not limited to: Left Atrial Pressure (LAP), Right Atrial Pressure (RAP), Left Ventricular Pressure Rise dP/dt_(max,L) (LVPR), Right Ventricular Pressure Rise dP/dt_(max,R) (RVPR), Pulmonary Artery Pressure (PAP), Left Ventricular Systolic Pressure (LVSP), Right Ventricular Systolic Pressure (RVSP).

BRIEF DESCRIPTION OF THE DRAWINGS

The below described embodiments with the references to the accompanying drawings present the features and advantages of the current invention. It has to be noted that being an example of a functional system the following implementation is not limited to mentioned devices/technologies that may be replaced by their similar modalities as long as the said modalities can produce the imaging data and maintain data connections to control units which, in turn, may be any computing devices restricted only by ability to run processing software and provide necessary data connections and user interfaces:

FIG. 1 depicts a schematic illustration of a blood pressure calibration procedure performed during clinical catheterization. The pressure sensor (101) is located inside the patient's heart or blood vessel (102) introduced by catheter (103) through a subclavian jugular or cephalic vein (104). The sensor is connected to pressure monitor (105), which is, in turn, connected to a computer, serving as the calibration control unit (106). The medical imaging device (107), connected to the calibration control unit (106) by wired or wireless connection (108), is performing a recording (109) of the patient's heart (102) where the sensor (101) is located. The calibration control unit (106) creates a simultaneous recording from both imaging device (107) and pressure monitor (105), synchronizes the data, performs the calculations and sends them to remote cloud or other specialized server (110) for storage or performing calculations.

FIG. 2 depicts the typical usage procedure of the pressure measurement method. The imaging device (201) connected by wired or wireless connection (202) to end-user control unit (203), in this case a smartphone, as an example, is pointed towards the patient's heart (204), for which the calibration was previously performed and performs a recording (205), sending it to the end-user control unit. The end-user control unit sends the data to the remote cloud server or other specialized server (206), where the calculations are performed based on previously recorded model and their results are displayed to the patient through the end-user control unit.

FIG. 3 depicts the typical case of usage procedure in presence of previously calibration model for the specific patient, who performs the measurement procedure (301), sending the data to remote cloud or other specialized server (302), which retrieves the stored calibration model (303) and calculates the result according to the said model.

FIG. 4 depicts the typical case of usage procedure without previous calibration model for the specific patient. The patient performs the recording procedure (401), sending further the data to remote cloud or other specialized server (402), which retrieves the stored calibration models (403) of other patients with similar physiological data (age, weight, height, diagnoses, etc.) and uses machine learning to calculate the result according to said models.

FIG. 5 depicts a single frame of imaging data of patient's heart (501) as it is received from imaging device displayed as 3d surface.

FIG. 6 depicts two frames of imaging data of patient's heart showing the difference between data at different time moments (601, 602).

FIG. 7 depicts the assembled T-Image (701) compiled from imaging data (702) with an appropriate time axis (703).

FIG. 8 depicts two frames of imaging data (801, 802) in different states of the heart with detected heart contour (803, 804), and the positions and contours of Right Atrium (805, 806), Left Atrium (807, 808), Right Ventricle (809, 810) and Left Ventricle (811, 812).

FIG. 9 depicts two frames of imaging data (901, 902) with separated contours of Right Atrium (903, 904).

FIG. 10 depicts the connection between pressure (1001) and state of heart chamber, in this case the Right Atrium (1002).

FIG. 11 depicts the process of creation of a Characteristic Image. A frame of imaging data (1101) is compressed (1102) using averaging or other invariant method to a single column (1103). In the same manner, the T-Image (1104) containing series of frames and a time axis (1105) is compressed to a Characteristic Image (1106) with number of columns identical to number of frames and the same time axis (1107).

FIG. 12 depicts the connection between pressure (1201) and the Characteristic Image (1202).

FIG. 13 depicts the definition of the LVEDP (left ventricular end-diastolic pressure) as seen from the pressure monitor (105). The measurement of LVEDP is made once per cardiac cycle, and is defined as the value of the left ventricular (LV) pressure (1301) at a moment along the time axis (1304) when the onset of isovolumetric contraction is registered (1306) positioned to the right from the peak of QRS complex (1305) on the ECG recording (1303). The onset of isovolumetric contraction of LV is associated with mitral valve closure and corresponds to the time moment when Left Ventricle End-Diastolic Pressure (LVEDP) is measured. The value of the pressure at this moment (1306) is roughly equivalent to the left atrial pressure (LA) (1302) at the same moment.

FIG. 14 depicts the high frequency algorithmic assessment of the LVEDP from Characteristic Image (1401). The method contains synchronous with T-image acquisition, LV pressure measurement (1403) along the time axis (1405) and the subsequent identification of the LVEDP curve (1404) in the Characteristic image (1402) at the frequency corresponding to the one of imaging device.

DESCRIPTION OF EMBODIMENTS

Specific embodiments or examples of the invention will now be described with reference to the accompanying drawings. This invention may, however, can be embodied in many different forms and should not be construed as limited to the embodiments demonstrated herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. The terminology used in the detailed description of the embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention.

The present description of the current invention is given with reference to blood vessels or a heart chambers as an example only. It should be born in mind however that the present invention is not limited strictly to a blood vessels or heart chambers, but can be easily adapted to any medium transparent for ultrasound or other waves with the need to measure pressure changes of the liquid flow. Examples include the lymphatic system, bile ducts, urinary ducts, subarachnoid space around the brain and spinal cord (Cerebrospinal fluid), inside or exterior of the lung in the chest wall, etc. for measuring pressures and dynamic progress thereof.

Alternatively or in addition to ultrasound in order to generate series of images to be analysed for the intra body pressure determination, other systems capable of highlighting inner physiological features and streaming image data in real time, for instance Echo Doppler, Magnetic Resonance Imaging (MRI), or ionizing radiation based imaging systems like Roentgen (X-Ray, Computer tomographic Imaging [CT]) can be provided as medical imaging modalities for generating the input for the pressure determination.

Additionally, while the present description refers to the usage of 2-dimensional cross-section ultrasound imaging of the investigated chamber as is produced by contemporary sensors, is not limited to it and can be utilized with different modalities that produce several 2-dimensional cross-sections or a full 3-dimensional representation of the investigated chamber.

In accordance with preferred embodiments a system comprises for example:

1) For the Calibration Process (FIG. 1)

-   -   a) At least one catheter based blood pressure sensor (101) with         analogue or digital data output connected to medical pressure         monitor (105). The said sensor is located inside the patient's         heart or blood vessel, such as pulmonary artery, (102)         introduced, for example, by catheter (103) through a subclavian,         jugular or cephalic vein (104). It is assumed, however, that         since the calibration procedure is performed during scheduled         clinical catheterization for the said patient, the sensor may be         already introduced into the problematic region as a part of a         procedure, and only its connection to the system through         items b) and d) is actually required.     -   b) Medical pressure monitor with analogue or digital data output         combined with optional oscilloscope digitalizing the output and         permitting to stream the output data into the calibration         control unit, preferably a computer (106). Note that this         functionality can be encapsulated inside either pressure monitor         or calibration control unit in alternative embodiments.     -   c) At least one medical imaging device, for example an         ultrasound probe (107) with wired or wireless digital output         permitting to stream the output data into the         computer/information receiving/processing/storage calibration         control unit (106). The said probe is pointed to the same body         region where the sensor (101) is located.     -   d) Calibration control unit, preferably a computer or a mobile         device equipped with hardware and software permitting         synchronization, recording, storage and processing of input data         from medical imaging device and medical pressure monitor. The         said calibration control unit performs a simultaneous recording         preferably of 30-60 seconds in time duration from both medical         imaging device and medical pressure monitor.

2) For the General (or post-calibration) Usage Process (FIG. 2)

-   -   a) At least one medical imaging device, for example an         ultrasound probe (201) with wired or wireless digital output         permitting to stream the output data into the         computer/information receiving/processing/storage end-user         control unit (203).     -   b) End-user control unit (203), preferably a computer or a         mobile device equipped with hardware and software permitting         recording, storage and processing of input data from medical         imaging device.

3) Optionally the system includes a remote cloud or other specialized server (110, 206, 302, and 402), operation of which permits both calibration control unit (106) and end-user control unit (203) to store, retrieve and exchange data if internet connection is available, but it is generally possible to transfer of the data by other means, directly between the devices or by physical medium.

4) During the Calibration Process, the software, positioned either on the Calibration control unit (106) or on remote cloud or other specialized server (110) processes the recorded data by using the algorithm described in items (7)-(8) and creates and stores a calculation model (303) for calculation of subsequent pressure results from medical imaging device recordings of the previously calibrated patient. This model is transferred directly or via the server to end-user control unit.

5) During the General (or post-calibration) Usage Process (FIG. 3, 4) the said calculation model (303) is accessed either locally or on server (302) by end-user control unit to calculate the patient's pressure during the subsequent pressure calculation according to the data recorded by the imaging device (202).

6) In absence of previous calibration model for the specific patient (FIG. 4) the patient performs the recording procedure (401), sending further the data to remote cloud or other specialized server (402), which retrieves the stored calibration models (403) of other patients with similar physiological data (age, weight, height, diagnoses, etc.) and uses machine learning to calculate the result according to said models. In this case use of a server is required.

7) The data recorded during the Calibration Procedure is processed as follows:

-   -   a) The data received from the imaging device decoded into image         frames (FIG. 5). The frames may be 2 or 3-dimensional, depending         on the imaging technology.     -   b) Each frame (FIG. 6) is marked with a time at which it was         recorded. In this example the difference between frames (601)         and (602) is about 0.5 second.     -   c) T-Image {T_(i)}_(i=1, . . . N) (FIG. 7) (701) is formed from         the data. It comprises an array of imaging data (702) linked to         an appropriate time axis (703).     -   d) The software determines the physiological features that can         be detected in the imaging data (FIG. 8). On the two frames         (801, 802) separated in FIG. 8 by 0.5 second the software         locates the heart (803, 804), and the positions and contours of         Right Atrium (805, 806), Left Atrium (807, 808), Right Ventricle         (809, 810) and Left Ventricle (811, 812).     -   e) If, for example, the sensor during the calibration was         located in the Right Atrium (FIG. 9) of the patient's heart, the         software separates the Right Atrium (903, 904) on each frame         (901, 902).     -   f) The software then converts the detected contour (903, 904)         into a set of coordinates {x_(j)}, representing the 3d or 2d         form of the target region, whichever is provided by the imaging         device. This coordinate set may contain any number of point         coordinates, depending on the processing power available to the         software and image resolution of the imaging device, with at         least two (the depths where the target region begins and where         it ends) required to make a pressure assessment.     -   g) The software then compares (FIG. 10) the changes in         coordinate sets in each frame (1002) to the changes in pressure         measured during calibration (1001) at the same times, and builds         a calculation model P(t_(i))=P(t_(i), {x_(j)}_(j=1, . . . M)         ^(i)⊂T_(i)), where P(t_(i)) is the measured pressure at time         t_(i) of each imaging frame.     -   h) The said model is stored in the calibration control unit and         later transferred to patient's end-user control unit using cloud         or other specialized server or directly or by any other means.

8) Additionally to the method described above in item (7) a simplified method of processing may be used which comprises of:

-   -   a) Conversion of T-Image into a Characteristic Image (FIG. 11).         Each frame {T_(i)}_(i=1, . . . N) of imaging data (1101) is         compressed (1102) using averaging or other invariant method to a         single column (1103). In the same manner, the T-Image (1104)         containing series of frames and a time axis (1105) is compressed         to a Characteristic Image (1106) with number of columns         identical to number of frames and the same time axis (1107).     -   b) In a process similar to item (7(d)-(f)) the software         determines the boundaries of the target images on the compressed         columns, determining the minimum required two (the depths where         the target region begins and where it ends), although using         various image processing techniques more information on the         region's form may be determined, and creates the calculation         model in similar way to item (7(g)). The dependency (FIG. 12)         between the sequence of compressed columns (1202) and the         synchronized pressure recording (1201) is clearly visible.

This method enables to greatly increase the speed of processing and reduces the computational power requirements while maintaining enough accuracy given the images are recorded from a similar angle to the calibration.

9) During General (or post-calibration) Usage, the patient

-   -   a) Uses the imaging device in the same manner as during the         calibration to make a recording of a given number of seconds of         the same region that was recorded during the calibration. The         doctor should provide necessary training for the patient to         remember the point to which the imaging device should be         directed.     -   b) The imaging device transmits by wired or wireless connection         the image sequence to the end-user control unit.     -   c) The end-user control unit retrieves the patient's model (if         the patient had undergone personal calibration) from internal         memory/cloud service/storage medium     -   d) If the patient did not undergo the personal calibration         procedure, the end-user control unit transmits the patient's         data such as height, weight, diagnosis, stored in similar way to         the cloud service or specialized server. The cloud service or         specialized server returns a model created using machine         learning based on the database of patients with similar         characteristics.     -   e) The software on end-user control unit then passes the images         obtained from the imaging device during the said recording in a         manner similar to items (7(d)-(f) or 8), obtaining the         coordinate set {x_(j)}.     -   f) Using the said coordinate set {x_(j)} and the model         P(t_(i))=P(t_(i), {x_(j)}_(j=1, . . . M) ^(i)⊂T_(i)), the         software calculates it's assessment of pressure and displays it         to the user.     -   g) The software may optionally transmit this assessment to the         server, display it to the doctor using doctor's dedicated system         and/or show system alerts if it detects abnormal values or         patterns.

10) Highlighting a diagnostic example, the system is capable of assessment and calculation of LVEDP (Left-Ventricular End-Diastolic Pressure) (FIG. 13) at the imaging device frequency (FIG. 14), by recording a movement of the mitral valve (1402). The method contains the LV pressure measurement (1403) along the time axis (1405) synchronous with T-image {T_(i)}_(i=1, . . . N) acquisition and the subsequent identification of the LVEDP curve (1404) in the Characteristic image {I_(i)}_(i=1, . . . N) (1402) which in combination with the fitting from items 7,8 above of the said measured pressure P_(i) to a given functional shape P_(i)=P(t_(i), {x_(j)}_(j=1, . . . K) ^(i)⊂I_(i)) provides the LVEDP pressure assessment at the imaging device frequency. LVEDP is the major marker of the left heart failure (CHF), myocardial infarction, tamponade, aortic regurgitation and others. In the same way the method permits to assess non-invasively during the subsequent Ultrasound recordings of the Right Ventricular (RV) pressure, the RVEDP—right ventricular end-diastolic pressure being the major marker of the right heart failure, cardiomyopathy, RV ischemia and infarction.

11) The other real time characteristics which can be measured or estimated using the above method include but not limited to: Left Atrial Pressure (LAP), Right Atrial Pressure (RAP), Left Ventricular Pressure Rise dP/dt_(max,L) (LVPR), Right Ventricular Pressure Rise dP/dt_(max,R) (RVPR), Pulmonary Artery Pressure (PAP), Pulmonary Capillary Wedge Pressure (PCWP), Left Ventricular Systolic Pressure (LVSP), Right Ventricular Systolic Pressure (RVSP).

12) The system includes software with at least the following capabilities:

-   -   a) Both control unit devices may be any computing devices         restricted only by ability to run processing software and         provide necessary data connections and user interfaces.     -   b) For the Calibration control unit:         -   i) Provide a real-time connection for data retrieval from             -   (1) Medical imaging device             -   (2) Pressure sensor(s) an/or a Pressure Monitor         -   ii) Display the images and pressure data acquired from said             devices, including image stream for targeting the region of             interest         -   iii) Provide assistance in targeting for the user on user             interface         -   iv) Perform a synchronized data recording of set of             arbitrary length         -   v) Store and transmit the acquired data to readable medium,             other devices or cloud server.         -   vi) Perform analysis and calculation of pressure model based             on acquired data.     -   c) For End-user control unit:         -   i) Provide a real-time connection for data retrieval from             Medical imaging device         -   ii) Display the images and pressure data acquired from said             device, including image stream for targeting the region of             interest         -   iii) Provide assistance in targeting for the user on user             interface         -   iv) Perform a recording of set or arbitrary length         -   v) Store and transmit the acquired data to readable medium,             other devices or cloud server.         -   vi) Store and retrieve the calculation mode from internal             memory, readable medium or the cloud server.         -   vii) Perform analysis and calculation of pressure based on             calculation model and acquired data.         -   viii) Detect anomalies and display alerts on user interface.     -   d) For cloud server or dedicated server system:         -   i) Store and retrieve patient data, recordings, models         -   ii) Provide patient data to respective doctors including             recording results, pressure trends, etc.         -   iii) Collect and provide cumulative models from patients             with similar characteristics for patients without personal             calibration         -   iv) Perform all analysis and calculations of end-user and             calibration control units (10(a)(vi), 10(b)(vii)).         -   v) Provide user interfaces for doctors and patients         -   vi) Provide connection interfaces for end-user and             calibration control units.

The present invention has been described using a non-limiting detailed description of various embodiments and examples thereof. It should be appreciated that the present invention is not limited by the above-described examples and that one ordinarily skilled in the art can make changes and modifications without deviation from the scope of the invention as will be defined below in the appended claims.

Below are listed some of the modifications, which are within the scope of invention as defined by the appended claims:

-   -   The pressure sensors can be combined with pressure monitor,         medical imaging device and calibration control unit into single         device.     -   In the same way medical imaging device can be combined with the         End User Control Unit into a single device.

It should also be appreciated that features disclosed in the foregoing description, and/or in the foregoing drawings and/or following claims both separately and in any combination thereof, be material for realizing the present invention in diverse forms thereof. When used in the following claims, the terms “comprise”, “include”, “have” and their conjugates mean, “including but not limited to”.

The present invention has been described above with reference to specific examples. However, other embodiments than the above described are equally possible within the scope of the invention. Different method steps than those described above, performing the method by hardware or software, may be provided within the scope of the invention. The different features and steps of the invention may be combined in other combinations than those described. The scope of the invention is only limited by the appended patent claims. 

1. A system and method for providing continuous non-invasive measurements and calculations of the dynamically changing pressures inside a person's body, said system comprising of ultrasound or other medical imaging device connected to an end-user control unit presumably computer or a mobile device, said end-user control unit records an initial image stream {J_(i)}_(i=1, . . . N) of cardiovascular movement of a said body from the said imaging device; processes the initial image stream {J_(i)}_(i=1, . . . N) generating corresponding T-image {T_(i)}_(i=1, . . . N) defined as a chronological union of said initial image stream {J_(i)}_(i=1, . . . N) with corresponding time stamps; said control unit then processes the T-Image {T_(i)}_(i=1, . . . N) to determine the oscillating traceable regions corresponding to cardiovascular features and records their form changing over time; said oscillating traceable region is defined as a region appearing on most images comprising the T-Image {T_(i)}_(i=1, . . . N) and corresponding to the physiological domain where the pressure is measured or calculated; said form changing corresponds to relative changes in the pressure in the said oscillating traceable regions; said relative changes in pressure comprise an independent diagnostic tool; said continuous non-invasive measurements and calculations of the dynamically changing pressures inside a said person's body can be performed at any time or place by directing the said imaging device connected to the said end-user control unit to the region of interest, such as the heart or heart chambers and performing a recording from which the said control unit will produce a calculated relative real-time pressure value series {P(t_(i))}_(i=1, . . . N); said end-user control unit is able to obtain the absolute pressure values as a function corresponding to the said form changing of the said oscillating traceable region; said function is obtained during either patient personal calibration procedure or using a database comprised of calibration process data for patients with similar physiology; said calibration procedure is performed during clinical catheterization as synchronized, simultaneous measurement of pressure values P_(i, i=1, . . . N) in the said oscillating traceable region(s) with a penetrating physical pressure measurement sensor(s) connected to a pressure monitor unit and a recording with said imaging device of the said oscillating traceable region; said pressure monitor unit and said imaging device being both controlled by calibration control unit; said calibration control unit is preferably a computer or a mobile device capable of connecting to both said imaging device and said pressure monitor unit connected to at least one pressure measurement sensor; said calibration procedure is followed by calibration process initiated by said calibration control unit. Said process includes, but is not limited to the identification of the said oscillating traceable regions inside the said T-Image recorded during said calibration procedure and fitting their movement to the pressure values P_(i) in these regions measured by the said penetrating physical pressure measurement sensors and processed by calibration control unit; in presence of the said calibration process, said continuous non-invasive measurements and calculations of the dynamically changing pressures inside a said person's body can be performed at any time or place by directing the said imaging device connected to the said end-user control unit to the same region as during the said calibration procedure and performing a recording which the said control unit will compare against the results of the said calibration process for the said patient and produce a calculated real-time pressure value series {P(t_(i))}_(i=1, . . . N); in absence of said calibration process, on the basis of the recorded image data for the said person the system is capable to estimate the said pressure using a database comprised of calibration process data for patients with similar physiology.
 2. A system of claim 1 for non-invasive measurement and calculation of a pressure inside a body, said system containing an external to the said body medical imaging unit capable of highlighting inner physiological features, preferably an ultrasound unit. Said imaging unit, having at least one transducer, preferably ultrasound transducer, arranged outside said body and radiating the beams into a target area inside said body. Said beams reflecting from said inner physiological features are registered by said imaging unit which performs reverse conversion of said reflected beam into image data. Said imaging unit having at least one communication protocol, wired or wireless, is connected to the said control unit, and transmits the obtained image stream {J_(i)}_(i=1, . . . N) in real time, as soon as each said image is registered to the said control unit over the said communication protocol.
 3. A system from claim 1 for non-invasive measurement and calculation of a pressure inside a body, said system containing a said calibration control unit, which is preferably a computer or a mobile device with a capability of simultaneous operational connection to the said medical imaging device and said pressure monitor unit connected to at least one said penetrating pressure sensor, and adapted to run a control and calibration software. Said software being configured to provide a graphical user interface (GUI) to register in synchronized, simultaneous manner the said image stream {J_(i)}_(i=1, . . . N) from the said medical imaging unit and said measured pressure values P_(i) from the said penetrating pressure sensor in real time, registering the times t_(i) for received data, generating said corresponding T-image {T_(i)}_(i=1, . . . N) and fitting a pressure calculation model to said measured or estimated pressure values P_(i)≈P(t_(i), {T_(i)}_(i=1, . . . N)). The said calibration control unit then transmits the said calculation model to said end-user control unit either directly or through optional connection to cloud service/internet. Optionally, the said calibration control unit may be combined with the medical imaging device from claim 2 and pressure sensors and pressure monitor from claim 1 into a single device.
 4. A system from claim 1 for non-invasive measurement and calculation of a pressure inside a body, said system containing a said end-user control unit, which is preferably a computer or a mobile device with a capability of operational connection to the said medical imaging device and adapted to run a control and calculation software. Said software being configured to provide a graphical user interface (GUI) to register the said image stream {J_(i)}_(i=1, . . . N) registering the times t_(i) for received data, generating said corresponding T-image {T_(i)}_(i=1, . . . N) and perform estimation of the said pressure as P_(i)=P(t_(i), {T_(i)}_(i=1, . . . N)) using the said pressure calculation model received from said calibration control unit. Said end-user control unit may optionally be able to establish a connection to optional cloud service or standalone server to transmit and receive said pressure calculation model. Optionally, the said end-user control unit may be combined with the medical imaging device from claim 2 into a single device.
 5. A method from claim 1 for non-invasive measurement and calculation of a pressure inside a body of patient, said method including optional calibration procedure. Said procedure performed on said patient in case of undergoing clinical catheterization for any medical, preferably Cardiological reason. During said catheterization a calibration system is used, which includes: Said calibration control unit from claims 1,3 Said medical imaging device from claims 1,2 Said pressure monitor unit from claim 1 At least one said penetrating pressure sensor from claim 1 The said calibration system is functional when the said medical imaging device and the said pressure monitor with attached said penetrating pressure sensor(s) are connected to the calibration control unit and the said unit is able to send and receive data from both connections. Said calibration procedure includes: early introduction of the said penetrating pressure sensor(s) into the said target oscillating traceable region(s); setting said medical imaging device into operation; providing a user interface, such as a graphical user interface (GUI) including an on-screen image, and displaying, highlighting inner physiological features; establishing a connection between the said calibration control unit, said medical imaging device and the said pressure monitor connected to least one said penetrating pressure sensor; pointing said medical imaging device in a direction to said target oscillating traceable region(s), where pressure measurement sensor(s) is located inside said patient's body, and holding in said position and/or adjusting said direction according to said displayed image until said region is visible on said image; switching the said calibration control unit into a recording mode of operation during which the said calibration control unit will perform a synchronized, simultaneous recording from the said imaging device and the said pressure monitor of the said oscillating traceable region(s) and the said pressure data from said penetrating pressure sensor(s) marking the time of received data; upon finishing the said recording, the calibration control unit will save and process the recorded data as the said image stream {J_(i)}_(i=1, . . . N) registering the times t_(i) for received data, generating said corresponding T-image {T_(i)}_(i=1, . . . N) and perform estimation of the said pressure creating a calculation model P_(i)=P(t_(i), {T_(i)}_(i=1, . . . N)). The said calibration control unit then transmits the said calculation model to said end-user control unit either directly or through optional connection to cloud service/internet.
 6. A method from claim 1 for non-invasive measurement and calculation of a pressure inside a body of patient, said method including the said calculation model from claims 3, 5 which is formed by assessing the size of said target oscillating traceable region(s) from each frame of the said T-image {T_(i)}_(i=1, . . . N) creating a set of coordinate parameters {x_(j)}_(j=1, . . . M) representing the said oscillating traceable region size and position at each time corresponding to each frame T_(i) of the said T-image {T_(i)}_(i=1, . . . N) and fitting the said measured pressure P_(i) to a given functional shape P_(i)=P(t_(i), {x_(j)}_(j=1, . . . M) ^(i)⊂T_(i)).
 7. A method from claim 1 for non-invasive measurement and calculation of a pressure inside a body of patient, said method including the said continuous measurements and calculations of the dynamically changing pressures inside a said person's body performed at any time or place by directing the said imaging device from claims 1, 2 connected to the said end-user control unit from claims 1, 4 to the same region as during the said calibration procedure and performing a recording which the said end-user control unit will assess the size and form of said target oscillating traceable region(s) from each frame of the said T-image {T_(i)}_(i=1, . . . N1) produced during the said recording, creating a set of coordinate parameters {x_(j)}_(j=1, . . . M) representing the said oscillating traceable region size, form and position at each time corresponding to each frame T_(i) of the said T-image {T_(i)}_(i=1, . . . N1). In case of presence of a calibration process from claim 5 for the current patient or from patients with similar physiological parameters as described in claim 1, the said end-user control unit will compare the said set of coordinate parameters against the resulting model fit from claim 6 of the said calibration process for the said patient and produce an estimate real-time pressure value series P(t_(i))=P(t_(i), {x_(j)}_(j=1, . . . M) ^(i)⊂T_(i)). In case of absence of the calibration process from claim 5 for the current patient or from patients with similar physiological parameters as described in claim 1, the said end-user control unit will provide an estimate of relative changes in the pressure value series.
 8. A system from claim 1 may contain an optional server or cloud service which can receive, store and manage said calculation models, perform calculation in lieu of the said end-user control units and use machine learning tools over stored databases to create models for said patients that had not undergone said calibration procedure using said calibration models created for patients with similar physiological parameters.
 9. A calculation model from claim 6 may include, but not limited to using a method of assessing the size of the said target oscillating traceable region(s) by using Characteristic (or Eigen-) Image which is defined as follows: The Characteristic image {I_(i)}_(i=1, . . . N) of the said T-image {T_(i)}_(i=1, . . . N) is defined as a chronological union of the averages of the rows or other invariants of the initial image series {T_(i)}_(i=1, . . . N) across each given depth, in the way that the first pixel-column I₁ (i=1) of the Characteristic image contains the averages over the rows or other invariants of the first image in time, the second pixel-column I₂ (i=2) of the Characteristic image contains the averages over the rows or other invariants of the second image in time, and finally the last pixel-column I_(N) (i=N) of the Characteristic image contains the averages over the rows or other invariants of the last image in time in the series. The invariants in the Characteristic images can be averages of the columns vertical or horizontal average gradients singular values or eigenvalues of each image packed into the Characteristic image as one matrix Fourier, Wavelet or other generalized decomposition images of the Characteristic images defined above.
 10. A calculation model from claim 6 when using the Characteristic Image {I_(i)}_(i=1, . . . N) from claim 8 is used to assess the size of said target oscillating traceable region(s) from each frame of the said T-image {T_(i)}_(i=1, . . . N) creating a set of coordinate parameters {x_(j)}_(j=1, . . . K) representing the said oscillating traceable region size and position at each time corresponding to each column I_(i) of the said Characteristic Image {I_(i)}_(i=1, . . . N) and fitting the said measured pressure P_(i) to a given functional shape P_(i)=P(t_(i), {x_(j)}_(j=1, . . . K) ^(i)⊂I_(i)).
 11. A system from claim 1 for non-invasive measurement and calculation of a pressure inside a body of patient, said system includes software including code segments for providing a data transfer and control connection to said medical imaging device from claims 1,2; providing a data transfer and control connection to said pressure monitor from claim 1; providing on a user interface, such as a graphical user interface (GUI) including an on-screen image, and displaying a data stream {J_(i)}_(i=1, . . . N) and further calculation results in said user interface; providing a recording of data stream {J_(i)}_(i=1, . . . N) received from the said medical imaging device and said pressure monitor; recording a time of data reception; forming a said time series T-Image {T_(i)}_(i=1, . . . N); creating a said calculation model P_(i)=P(t_(i), {T_(i)}_(i=1, . . . N)); using the said calculation model on recorded data of subsequent recordings; storing the data, calculation models for subsequent usage; transmitting and receiving the data and calculation models to/from said cloud storage from claim
 8. 